Quantitative Researcher

Goliath Partners Inc.; New York, Northern (NY, KY); On-site; USD 350,000 - 1,500,000; Full time

Benefits offered by this job

Sign-on bonus

Buyout option

Performance bonus

P&L participation

Non-compete wait up to 15 months

Job summary

Goliath Partners Inc. in New York seeks a Lead Quantitative Researcher to scale high-frequency option vol strategies. You will research HFT option vol strategies across global markets, develop signals, and own research from hypothesis to live deployment.

The ideal candidate has proven quantitative research experience in options, volatility, and market microstructure, with strong Python skills (C++ a plus). The role offers a substantial compensation package and potential P&L participation.

Qualifications

• Proven quantitative research experience in options, volatility, market making, or HFT.
• Expertise in derivatives pricing, statistics, time-series analysis, and market microstructure.
• Strong Python skills; C++ (LLMs and C++ a plus) is a plus.

Responsibilities

• Research HFT option vol strategies across global markets.
• Develop signals using volatility surfaces, order-book dynamics, market microstructure, and cross-asset data.
• Improve options pricing, volatility forecasting, execution, hedging, and real-time risk models.
• Own research from hypothesis and backtesting through live deployment.

Skills

Quantitative research

Options/volatility

Derivatives pricing

Statistics

Time-series analysis

Market microstructure

Python

C++

Education

PhD or MSc in a quantitative discipline

Tools

C++

Job description

Lead Quantitative Researcher [HFT Options & Vol]

A leading systematic fund in New York is expanding after generating approximately $4.5B in profits last month. The firm is hiring a Lead Quantitative Researcher to scale high-frequency option vol strategies.

Compensation:

• $350K base
• $1M to $1.5M guaranteed packages.
• Sign-on/buyout, performance bonus, and potential P&L participation
• Will wait up to 15 months for a non competes

Responsibilities:

• Research HFT option vol strategies across global markets.
• Develop signals using volatility surfaces, order-book dynamics, market microstructure, and cross-asset data.
• Improve options pricing, volatility forecasting, execution, hedging, and real-time risk models.
• Own research from hypothesis and backtesting through live deployment.

Ideal Candidate:

• Proven quantitative research experience in options, volatility, market making, or HFT.
• Expertise in derivatives pricing, statistics, time-series analysis, and market microstructure.
• Strong Python skills; (LLMs and C++ are a plus not a requirement)
• Track record of translating research into profitable trading strategies.
• Advanced degree in a highly quantitative discipline